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---
license: other
library_name: transformers
datasets:
- ise-uiuc/Magicoder-OSS-Instruct-75K
- ise-uiuc/Magicoder-Evol-Instruct-110K
license_name: deepseek
pipeline_tag: text-generation
base_model: ise-uiuc/Magicoder-S-DS-6.7B
tags:
- TensorBlock
- GGUF
---
<div style="width: auto; margin-left: auto; margin-right: auto">
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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## ise-uiuc/Magicoder-S-DS-6.7B - GGUF
This repo contains GGUF format model files for [ise-uiuc/Magicoder-S-DS-6.7B](https://huggingface.co/ise-uiuc/Magicoder-S-DS-6.7B).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
<div style="text-align: left; margin: 20px 0;">
<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
Run them on the TensorBlock client using your local machine ↗
</a>
</div>
## Prompt template
```
<｜begin▁of▁sentence｜>You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
@@ Instruction
{prompt}
@@ Response
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Magicoder-S-DS-6.7B-Q2_K.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q2_K.gguf) | Q2_K | 2.360 GB | smallest, significant quality loss - not recommended for most purposes |
| [Magicoder-S-DS-6.7B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q3_K_S.gguf) | Q3_K_S | 2.747 GB | very small, high quality loss |
| [Magicoder-S-DS-6.7B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q3_K_M.gguf) | Q3_K_M | 3.073 GB | very small, high quality loss |
| [Magicoder-S-DS-6.7B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q3_K_L.gguf) | Q3_K_L | 3.351 GB | small, substantial quality loss |
| [Magicoder-S-DS-6.7B-Q4_0.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q4_0.gguf) | Q4_0 | 3.564 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Magicoder-S-DS-6.7B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q4_K_S.gguf) | Q4_K_S | 3.593 GB | small, greater quality loss |
| [Magicoder-S-DS-6.7B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q4_K_M.gguf) | Q4_K_M | 3.802 GB | medium, balanced quality - recommended |
| [Magicoder-S-DS-6.7B-Q5_0.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q5_0.gguf) | Q5_0 | 4.334 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Magicoder-S-DS-6.7B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q5_K_S.gguf) | Q5_K_S | 4.334 GB | large, low quality loss - recommended |
| [Magicoder-S-DS-6.7B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q5_K_M.gguf) | Q5_K_M | 4.456 GB | large, very low quality loss - recommended |
| [Magicoder-S-DS-6.7B-Q6_K.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q6_K.gguf) | Q6_K | 5.151 GB | very large, extremely low quality loss |
| [Magicoder-S-DS-6.7B-Q8_0.gguf](https://huggingface.co/tensorblock/Magicoder-S-DS-6.7B-GGUF/blob/main/Magicoder-S-DS-6.7B-Q8_0.gguf) | Q8_0 | 6.671 GB | very large, extremely low quality loss - not recommended |
## Downloading instruction
### Command line
Firstly, install Huggingface Client
```shell
pip install -U "huggingface_hub[cli]"
```
Then, downoad the individual model file the a local directory
```shell
huggingface-cli download tensorblock/Magicoder-S-DS-6.7B-GGUF --include "Magicoder-S-DS-6.7B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
```shell
huggingface-cli download tensorblock/Magicoder-S-DS-6.7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|